NVIDIA
SeniorGPUArchitect
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior GPU Architect at NVIDIA. Skills: GPU architecture, CPU System Architecture, Computer Architecture, modeling, C++, Python. Develop GPU architecture innovations and improvements, optimizing along the axes of scalability/modularity, performance, area, yield, effort, and schedule. Develop and enhance chip design infrastructure, including functional models and yield simulators, testbench components and analysis tools, to evaluate configurations under different constraints”
What You'll Achieve.
optimize along the axes of scalability/modularity, performance, area, yield, effort, and schedule; evaluate configurations under different constraints; optimize chip yield and performance; validate choices against performance, cost, and scalability targets
Industry & Context.
problem-solving and debugging skills; track record of driving issues to closure; Outstanding problem-solving skills with a focus on optimizing performance, area, complexity, and power
What They're Looking For.
Must Have
Bachelors/Master’s/PhD in Computer Engineering, Computer Science or related fields (or equivalent experience), A minimum of 10 years of relevant work experience in GPU or CPU System Architecture development, Proficient programming skills in C++ and Python, Solid background in Computer Architecture with experience in modeling, communication and interpersonal skills, problem-solving and debugging skills, with a track record of driving issues to closure
Nice to Have
Experience with GPU architecture and/or Network-on-Chip (NoC)/Interconnect, Knowledgeable in system level functions such as reset and boot, DFT, Consistent track record of efficiently implementing complex architectural features, Outstanding problem-solving skills with a focus on optimizing performance, area, complexity, and power
What You'll Do.
Develop GPU architecture innovations and improvements
optimizing along the axes of scalability/modularity
Develop and enhance chip design infrastructure
including functional models and yield simulators
testbench components and analysis tools
to evaluate configurations under different constraints
test plans and testing infrastructure for new architectures/ features
Implement and maintain functional
Document architecture work with ASIC design
and VLSI teams to review and explore trade-offs
How You'll Work.
Team & Collaboration
Work in a matrixed environment, across the different modeling teams; Collaborate with other functional teams (Design, Floorplan, Packaging and Systems Engineering, etc); dynamic, collaborative, distributed team
Communication Scope
communication and interpersonal skills
Full Job Description
This is an outstanding opportunity to join a world-class team and play a pivotal role in crafting the future of GPU technology. At NVIDIA, you will work with dedicated individuals in an inclusive and collaborative environment where your hardworking nature will drive flawless execution and ambitious projects. **What you will be doing:** * Develop GPU architecture innovations and improvements, optimizing along the axes of scalability/modularity, performance, area, yield, effort, and schedule. * Develop and enhance chip design infrastructure, including functional models and yield simulators, testbench components and analysis tools, to evaluate configurations under different constraints. * Develop tests, test plans and testing infrastructure for new architectures/ features * Work in a matrixed environment, across the different modeling teams, to document, design, develop tools to optimize chip yield and performance * Implement and maintain functional, performance, and yield models * Document architecture specifications; work with ASIC design, software, and VLSI teams to review and explore trade-offs, define solutions, and track progress. * Collaborate with other functional teams (Design, Floorplan, Packaging and Systems Engineering, etc) to validate choices against performance, cost, and scalability targets. * Guide the improvement of functional verification tools and expand other resources to support future GPU architectures **What we need to see:** * Bachelors/Master’s/PhD in Computer Engineering, Computer Science or related fields (or equivalent experience) * A minimum of 10 years of relevant work experience in GPU or CPU System Architecture development * Proficient programming skills in C++ and Python. * Solid background in Computer Architecture with experience in modeling * Strong communication and interpersonal skills, as well as the ability to thrive in a dynamic, collaborative, distributed team. * Strong problem-solving and debugging skills, with a track record
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